What Is Palantir Ontology? Designing an Operational Layer
What you’ll learn
- The general meaning of ontology and the additional operational role Palantir Ontology introduces
- How business items, relationships, calculations, change procedures, permissions, and user screens connect
- The boundaries among databases, knowledge graphs, RAG, and the rules and runtime environment that guide AI work
- How to scope a PoC across business items, change procedures, permissions, and records
Palantir Ontology Manages Business Data and Operations in One Layer
Palantir Ontology is an operational layer that manages business entities and relationships together with calculations, change procedures, permissions, and operation history. Moving an equipment inspection forward, for example, requires parts inventory, change conditions, execution authority, and a record of the update. Comparing this scope with RAG and knowledge graphs helps identify when an Ontology evaluation is worthwhile.
By the end of this article, you will have practical criteria for answering “Under what conditions should Palantir Ontology be evaluated as an operational layer connecting business decisions and execution?” in your own context.
An Ontology Defines Business Concepts, Relationships, and Constraints
In information science, an ontology is an explicit knowledge representation of the concepts, relationships, and constraints relevant to a domain. The term originated in philosophy as a theory of existence. AI researchers adopted it for knowledge systems in the 1980s, and the definition “an explicit specification of a conceptualization” became influential in the 1990s.[1]
OWL, the W3C Web Ontology Language for logically representing complex concepts and relationships, allows software to check knowledge consistency and make implicit knowledge explicit.[2] In this context, an ontology primarily defines what exists and how those things relate.
Palantir extends the scope to business execution. Its documentation describes Ontology as an operational layer that connects integrated datasets, virtual tables, and models to real-world counterparts such as equipment, products, customer orders, and financial transactions.[3] It is therefore more useful to view Palantir Ontology as a product architecture that connects a semantic model to operational applications and change processes, rather than as a direct productization of academic ontology.
Define Business Entities and Relationships, Then Connect Calculations and Controlled Changes
In Palantir Ontology, Objects, Properties, and Links represent business entities such as equipment and orders, their state, and their relationships. Functions and Actions represent calculations, decisions, and change procedures. Palantir documentation calls the first group Semantic Elements and the second Kinetic Elements.[3]
| Element | Role | Maintenance question |
|---|---|---|
| Business item (Object) | A kind of item, such as equipment, orders, or customers, and each actual item | Which number and rule identify the same item? |
| Information about an item (Property) | Status, quantity, deadline, and similar information | Are meaning, unit, and update source consistent? |
| Relationship between items (Link) | Connections such as order-to-customer or equipment-to-site | Can the evidence and valid period of the relationship be traced? |
| Calculation or decision (Function) | Calculations, decisions, and estimates under different conditions | Can inputs, version, and exceptions be tested? |
| Change procedure (Action) | Creation, update, approval, or connection to another service | Who may change what, and under which conditions? |
| Permission based on the situation | Permissions applied to items, information, and operations | Can permission to see and permission to change be separated? |
Objects, Properties, and Links provide the business entities and current state that a workflow reads. Functions and Actions define what can be calculated and which changes are allowed for those entities. A Palantir Action Type defines input parameters, Ontology edits, side effects such as notifications, and execution conditions. The same Action logic can then be reused across user-facing applications.[4]
The Workflow Connects Current State, Controlled Changes, and Audit Records
The main distinction between Palantir Ontology and a read-only semantic layer is that it can connect current-state retrieval, option comparison, permissioned changes, and operation records in one workflow. This article reorganizes the official components into four stages.
- Check the current state: Retrieve the current state from business items, their information, and their relationships
- Compare options: Use calculations and trial conditions to estimate alternatives and impact
- Execute a change: Apply a change only when the required conditions and permissions are satisfied
- Review the change record: Use operation history to determine who changed what and when
A Palantir operational application, meaning a business application that supports a decision and writeback in addition to displaying information, can show the Ontology’s current state, test proposed changes in a Scenario, and commit a decision through an Action.[5] Action submission criteria can combine the current user, input values, and Object state to reject changes that do not satisfy the configured conditions.[6]
Consider a maintenance team deciding whether to bring forward an inspection for equipment at high risk of stopping. Equipment, failures, work orders, and parts inventory are connected through Objects and Links. A Function calculates risk and impact, and a coordinator compares candidate dates. An Action updates the work order only after confirming that the equipment is operating, parts are reserved, and the operator has approval authority. An Action Log can retain the decision and its relationship to edited Objects.[7]
The graph itself is not the primary value. Meaning, calculation, operations, and controls refer to the same business concepts, reducing the need for each application or AI agent to implement a separate version of the rules.
Choose a Smaller System When Document Search or Relationship Mapping Is Enough
Palantir Ontology is not one feature that replaces several technologies. Comparing the problem solved at each layer makes over-adoption easier to avoid.
| Option | Primary question | What it stores or defines | What it does not handle well by itself |
|---|---|---|---|
| Database and its blueprint | Where and in which format is data stored? | Tables, fields, text or number formats, input restrictions | Business vocabulary and decision procedures shared across systems |
| Shared definitions for analysis | How are measurements and terms standardized for analysis? | Measurements, classifications, aggregation methods | Changing business data and recording the change |
| Traceable relationship record | How are actual items related? | Items, connections, and information about items | Who may change state under which conditions |
| Related-document retrieval (RAG) | How is information relevant to a question retrieved? | Parts of documents, numbers representing similarity in meaning, search results | Authoritative business relationships, data updates, operational permissions |
| Palantir Ontology | How is state understood and connected to decisions and controlled change? | Items, relationships, calculations, change procedures, permissions | Improving source-data quality or creating agreement among accountable business owners |
| AI work environment | How are AI procedures and checks made more consistent? | Instructions, tools, evaluations, approvals, execution environment | A shared model of enterprise concepts connected to operational data |
The AWS Context Ontology Accelerator article focuses on a context layer that supplies meaning and relationships to AI agents, GraphRAG, and operating conditions on AWS. This article is limited to the Palantir-specific workflow connecting Actions, Functions, operational applications, permissions, and Action Logs from a decision through its change record.
If the requirement is document search and summarization, RAG provides a smaller starting architecture. If the task only needs relationship traversal across systems, a knowledge graph connected to existing applications may also fit. Ontology adds clearer value when multiple workflows must reuse the same Objects, Links, Functions, Actions, and permission controls.
Viewing and Change Permissions Are Configured Separately
Sharing an operational layer also expands the impact of model changes. An adoption decision should establish definition ownership and change authority, not only data connectivity.
In Palantir’s current permission model, permissions to view, edit, and manage Ontology resources are distinct from access to actual Object data. Viewing an Object Type definition does not grant access to Object values without access to the backing data or the applicable Object security policy. Editing Links or Actions also requires edit access to related Ontology resources.[8]
This separation requires at least the following responsibilities.
- Concept Owner: Approves business definitions, identity, and retirement conditions for Objects and Links
- Logic Owner: Maintains the basis, version, and test cases for Functions
- Action Owner: Approves inputs, edited entities, submission criteria, and side effects
- Security Owner: Verifies visibility and execution permissions for Objects, Properties, and Actions
- Application Owner: Manages the Ontology scope used by Workshop or custom applications and the impact of changes
The Ontology SDK (OSDK) provides a selected subset of an Ontology as a TypeScript or Python SDK, allowing an external application to retrieve Objects, apply Actions, and call Functions.[9] This expands the application surface, but it also means that Ontology changes may affect several applications. Version changes to Objects or Actions require regression checks across applications and business procedures, not only data pipelines.
Scope a Pilot Around Business Entities, Changes, Permissions, and Records
A PoC, or limited proof of feasibility and value, should begin with one recurring decision rather than an enterprise-wide ontology. The following decision sheet is an article-specific framework.
| Perspective | Define in the PoC | Minimum evidence | Condition to defer |
|---|---|---|---|
| Business entities and relationships | Items, information about them, and relationships required for the decision | Item identifiers, update sources, relationship evidence, data owner | One table or one document completes the task |
| Calculations and change procedures | Required calculations, change procedures, and exception conditions | Inputs and outputs, test cases, execution conditions, destination of the change | Read-only analysis meets the requirement |
| Permissions | Who can see and execute what | Visibility and execution tests for representative roles | Source-system permissions cannot be mapped |
| Records | How the decision and change are traced | Operation record, reason for the decision, related items, recovery procedure | Change owner and record requirements are undefined |
The PoC completion condition is not simply a working screen. For a representative decision, the system must retrieve the required state, compare options, apply a change within permissions and execution conditions, and make its basis traceable afterward. If one of these perspectives is incomplete, fill the missing responsibility and evidence before expanding the Ontology.
An existing data mart, semantic layer, RAG system, or workflow product may keep maintenance scope smaller when business concepts are not reused across applications, no writeback occurs, or relationship traversal is rare. Evaluate Palantir Ontology when the organization needs to operate decisions and execution continuously through the same business model.
Summary: Evaluate Ontology When Workflows Must Share Changes, Permissions, and Records
Palantir Ontology extends the general idea of concepts and relationships into an operational layer connected to Functions, Actions, Security, operational applications, and Action Logs. Its distinction from a knowledge graph or RAG is less about data representation and more about whether a system connects current-state checks, option comparison, governed changes, and operation records through the same business model.
Start an evaluation with one recurring decision and complete the business-entity, change-procedure, permission, and record perspectives in the decision sheet. A smaller architecture remains preferable when read-only search or analytics meets the requirement. Ontology becomes meaningful as an operational layer when these perspectives must be shared across multiple workflows and applications.
References
- Tom Gruber, Ontology, Encyclopedia of Database Systems, 2009
- W3C, Web Ontology Language (OWL), December 11, 2012
- Palantir, Overview — Ontology, 2026
- Palantir, Overview — Action types, 2026
- Palantir, What is an operational application?, 2026
- Palantir, Submission criteria, 2026
- Palantir, Action log, 2026
- Palantir, Ontology permissions, 2026
- Palantir, Overview — App building, 2026
For the latest releases and updates, check the official website and official documentation.